About this Course
최근 조회 154,862

다음의 1/6개 강좌

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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

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완료하는 데 약 16시간 필요

권장: 3 weeks of study, 5-6 hours/week...


자막: 아랍어, 한국어, 영어, 힌디어, 페르시아어

귀하가 습득할 기술

Big DataApache HadoopMapreduceCloudera

다음의 1/6개 강좌

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 16시간 필요

권장: 3 weeks of study, 5-6 hours/week...


자막: 아랍어, 한국어, 영어, 힌디어, 페르시아어

강의 계획 - 이 강좌에서 배울 내용

완료하는 데 20분 필요


Welcome to the Big Data Specialization! We're excited for you to get to know us and we're looking forward to learning about you!

2 videos (Total 3 min), 2 readings
2개의 동영상
Tell us about yourself and learn about your classmates20
2개의 읽기 자료
By the end of this course you will be able to...2m
Optional: Watch this fun video about the San Diego Supercomputer Center!10m
완료하는 데 4시간 필요

Big Data: Why and Where

Data -- it's been around (even digitally) for a while. What makes data "big" and where does this big data come from?

13 videos (Total 77 min), 13 readings, 1 quiz
13개의 동영상
Applications: What makes big data valuable11m
Example: Saving lives with Big Data6m
Example: Using Big Data to Help Patients10m
A Sentiment Analysis Success Story: Meltwater helping Danone1m
Getting Started: Where Does Big Data Come From?2m
Machine-Generated Data: It's Everywhere and There's a Lot!3m
Machine-Generated Data: Advantages4m
Big Data Generated By People: The Unstructured Challenge5m
Big Data Generated By People: How Is It Being Used?10m
Organization-Generated Data: Structured but often siloed7m
Organization-Generated Data: Benefits Come From Combining With Other Data Types4m
The Key: Integrating Diverse Data5m
13개의 읽기 자료
Did you know?: 25 facts about big data10m
Slides: What Launched the Big Data Era?10m
Slides: Applications: What Makes Big Data Valuable?10m
Slides: Saving Lives With Big Data10m
Slides: Using Big Data to Help Patients10m
Extra Resources10m
Slides: Machine-Generated Data: It's Everywhere and There's a Lot!10m
Slides: Machine-Generated Data: Advantages10m
Slides: Big Data Generated By People: The Unstructured Challenge10m
Slides: Big Data Generated By People: How is it Being Used?10m
Slides: Organization-Generated Big Data: Structured But Often Siloed10m
Slides: Organizaton-Generated Big Data: Benefits10m
Slides: The Key - Integrating Diverse Data10m
1개 연습문제
Why Big Data and Where Did it Come From?38m
완료하는 데 2시간 필요

Characteristics of Big Data and Dimensions of Scalability

You may have heard of the "Big Vs". We'll give examples and descriptions of the commonly discussed 5. But, we want to propose a 6th V and we'll ask you to practice writing Big Data questions targeting this V -- value.

7 videos (Total 34 min), 9 readings, 1 quiz
7개의 동영상
Characteristics of Big Data - Volume5m
Characteristics of Big Data - Variety5m
Characteristics of Big Data - Velocity6m
Characteristics of Big Data - Veracity6m
Characteristics of Big Data - Valence2m
The Sixth V: Value4m
9개의 읽기 자료
What does astronomical scale mean?10m
A Small Definition of Big Data10m
Slides: Getting Started - Characteristics of Big Data10m
Slides: Characteristics of Big Data - Volume10m
Slides: Characteristics of Big Data - Variety10m
Slides: Characteristics of Big Data - Velocity10m
Slides: Characteristics of Big Data - Veracity10m
Slides: Characteristics of Big Data - Value10m
Slides: Characteristics of Big Data - Valence10m
1개 연습문제
V for the V's of Big Data14m
완료하는 데 4시간 필요

Data Science: Getting Value out of Big Data

We love science and we love computing, don't get us wrong. But the reality is we care about Big Data because it can bring value to our companies, our lives, and the world. In this module we'll introduce a 5 step process for approaching data science problems.

11 videos (Total 66 min), 12 readings, 1 quiz
11개의 동영상
Building a Big Data Strategy9m
How does big data science happen?: Five Components of Data Science9m
Asking the Right Questions3m
Steps in the Data Science Process3m
Step 1: Acquiring Data6m
Step 2-A: Exploring Data4m
Step 2-B: Pre-Processing Data8m
Step 3: Analyzing Data8m
Step 4: Communicating Results4m
Step 5: Turning Insights into Action2m
12개의 읽기 자료
Five P's of Data Science10m
Slides: Getting Value Out of Big Data10m
Slides: Building a Big Data Strategy10m
Slides: The Five P's of Data Science10m
Slides: Asking the Right Questions10m
Slides: Steps in the Data Science Process10m
Slides: Step 1 - Acquiring Data10m
Slides: Step 2A-Exploring Data10m
Slides: Step 2B-Preprocessing Data10m
Slides: Step 3-Data Analysis10m
Slides: Step 4-Communicating Results10m
Slides: Step 5-Turning Insights Into Action10m
1개 연습문제
Data Science 10120m
완료하는 데 1시간 필요

Foundations for Big Data Systems and Programming

Big Data requires new programming frameworks and systems. For this course, we don't programming knowledge or experience -- but we do want to give you a grounding in some of the key concepts.

4 videos (Total 19 min), 4 readings, 1 quiz
4개의 동영상
What is a Distributed File System?6m
Scalable Computing over the Internet4m
Programming Models for Big Data6m
4개의 읽기 자료
Slides: Getting Started-Why Worry About Foundations?10m
Slides: What is a Distributed File System?10m
Slides: Scalable Computing Over the Internet10m
Slides: Programming Models for Big Data10m
1개 연습문제
Foundations for Big Data20m
완료하는 데 5시간 필요

Systems: Getting Started with Hadoop

Let's look at some details of Hadoop and MapReduce. Then we'll go "hands on" and actually perform a simple MapReduce task in the Cloudera VM. Pay attention - as we'll guide you in "learning by doing" in diagramming a MapReduce task as a Peer Review.

11 videos (Total 66 min), 8 readings, 3 quizzes
11개의 동영상
The Hadoop Ecosystem: Welcome to the zoo!7m
The Hadoop Distributed File System: A Storage System for Big Data7m
YARN: A Resource Manager for Hadoop5m
MapReduce: Simple Programming for Big Results12m
When to Reconsider Hadoop?4m
Cloud Computing: An Important Big Data Enabler6m
Cloud Service Models: An Exploration of Choices4m
Value From Hadoop and Pre-built Hadoop Images3m
Copy your data into the Hadoop Distributed File System (HDFS)4m
Run the WordCount program5m
8개의 읽기 자료
MapReduce in the Pasta Sauce Example10m
Slides for Getting Started With Hadoop10m
Downloading and Installing the Cloudera VM Instructions (Mac)10m
Downloading and Installing the Cloudera VM Instructions (Windows)10m
Copy your data into the Hadoop Distributed File System (HDFS) Instructions10m
Run the WordCount program Instructions10m
How do I figure out how to run Hadoop MapReduce programs?10m
2개 연습문제
Intro to Hadoop26m
Running Hadoop MapReduce Programs Quiz4m
1247개의 리뷰Chevron Right


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Introduction to Big Data의 최상위 리뷰

대학: PBMay 25th 2018

A step by step approach stating from basic big data concept extending to Hadoop framework and hands on mapping and simple MapReduce application development effort.\n\nVery smooth learning experience.

대학: RGJul 14th 2017

First of all i would like to take this opportunity to thanks the instructors the course is well structured and explained the foundations with real world problems with easy to understand the concepts.



Ilkay Altintas

Chief Data Science Officer
San Diego Supercomputer Center

Amarnath Gupta

Director, Advanced Query Processing Lab
San Diego Supercomputer Center (SDSC)

캘리포니아 샌디에고 대학교 정보

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

빅 데이터 전문 분야 정보

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. ********* Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data....
빅 데이터

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